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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 24 hours ago
, and reinforcement learning. Duties and Responsibilities A Postdoctoral Fellow (""postdoc"") is a professional apprenticeship designed to provide recent Ph.D. recipients with an opportunity to develop
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Have you completed your PhD? Are you eager to enrich knowledge on biodiversity as a postdoc? Then Naturalis in Leiden is the place for you. Pursuing a postdoc at Naturalis means working on research
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learning. The postdoc will also teach two mathematics courses per year (1 per semester). The appointment is a one-year position with a possibility for an annual renewal of up to 3 years in total
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intelligence (AI) residency) to advance scientific machine learning for clinical oncology. The project builds a hybrid framework that couples an existing quantitative systems pharmacology (QSP) model of cancer
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cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been explored extensively. You will be part of a
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Mathematics Computational Research Division (AMCR) has an immediate opening in the Quantum Information Science and Technology Group (QuIST ) for a Postdoc Follow in support of The Advanced Quantum Testbed (AQT
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 1 day ago
expertise in one or more of a broad range of computational methods including but not limited to: machine learning / AI, spatial computing, computational creativity, text encoding, social media analysis
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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental